1. Codifying the client's interactions
DBS faced challenges in keeping track of conversations and interactions between relationship managers and clients, which resulted in lost context and accountability issues. To address this, an unstructured text field was introduced with topical tags to encourage documentation of engagements. This approach enables capturing essential user information without overburdening the relationship managers, while training the data model with codified conversation tags.
2. Feedback loop for the AI model
An AI model was created to provide personalized insights and suggestions for each client, helping the relationship managers to contextualize their conversations and giving them angles to approach their client, rather than just another product/sales lead. To ensure continuous improvement of the data model, a feedback loop was created for relationship managers to rate these suggestions, providing them with tags to give more context on why the suggestion was good or bad.
3. Service requests management
To better serve customers, relationship managers must attend to service requests promptly. A service request can refer to a customer's request for assistance or support in relation to their banking needs. In order to keep track of these service requests, a view was created to provide an overview of open requests assigned to the relationship manager. The view displays each request's urgency and corresponding service level agreement, enabling relationship managers to prioritize their tasks effectively.
